Search results for: fire weather index

Authors: Marcus Bellett-Travers

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Different modelling approaches have been used to determine or predict yield of crops in different geographies. Central to the methodologies are the presumption that it is the absolute yield of the crop in a given location that is of the highest priority to those requiring information on crop productivity. Most individuals, companies and organisations within the agri-food sector need to be able to balance the supply of crops with the demand for them. Different modelling approaches have been used to determine and predict crop yield. The growing need to ensure certainty of supply and stability of prices requires an approach that describes the risk in producing a crop. A review of current methodologies to evaluate the risk to food production from changes in the weather and climate is presented.

Keywords: crop production, risk, climate, modelling

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Authors: Samaneh Abolli, Mahmood Alimohammadi

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The survey analyzed 71 bottled water brands in Tehran, Iran, examining 10 physicochemical parameters and 16 heavy metals. The water quality index (WQI) approach was used to assess water quality, and methods such as carcinogen risk (CR) and hazard index (HI) were employed to evaluate health risks. The results indicated that the bottled water had good quality overall, but some brands were of poor or very poor quality. The study also revealed significant human health risks, especially for children, due to the presence of minerals and heavy metals in bottled water. Correlation analyses and risk assessments for various substances were conducted, providing valuable insights into the potential health impacts of the analyzed bottled water.

Keywords: bottled wate, rwater quality index, health risk assessment, contamination degree, heavy metal evaluation index

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Authors: Sara Ali Alokley, Mansour Saleh Albarrak

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This paper investigates the dependency or clustering of extremes in the financial returns data by estimating the extremal index value θ∈[0,1]. The smaller the value of θ the more clustering we have. Here we apply the method of Ferro and Segers (2003) to estimate the extremal index for a range of threshold values. We compare the dependency structure of extremes in the developed and emerging markets. We use the financial returns of the stock market index in the developed markets of US, UK, France, Germany and Japan and the emerging markets of Brazil, Russia, India, China and Saudi Arabia. We expect that more clustering occurs in the emerging markets. This study will help to understand the dependency structure of the financial returns data.

Keywords: clustring, extremes, returns, dependency, extermal index

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Authors: Fatima Khurshid, Noor Ul Ain, Syed Abdul Rehman Kashif, Zainab Riaz, Abdullah Usman Khan, Muhammad Imran

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As the world is moving towards extra-high voltage (EHV) and ultra-high voltage (UHV) power systems, the performance requirements of power transformers are becoming crucial to the system reliability and security. With the transformers being an essential component of a power system, low health index of transformers poses greater risks for safe and reliable operation. Therefore, to meet the rising demands of the power system and transformer performance, researchers are being prompted to provide solutions for enhanced thermal and electrical properties of transformers. This paper proposes an approach to improve the health index of a transformer by using nano-technology in conjunction with bio-degradable oils. Vegetable oils can serve as potential dielectric fluid alternatives to the conventional mineral oils, owing to their numerous inherent benefits; namely, higher fire and flashpoints, and being environment-friendly in nature. Moreover, the addition of nanoparticles in the dielectric fluid further serves to improve the dielectric strength of the insulation medium. In this research, using the finite element method (FEM) in COMSOL Multiphysics environment, and a 2D space dimension, three different oil samples have been modelled, and the electric field distribution is computed for each sample at various electric potentials, i.e., 90 kV, 100 kV, 150 kV, and 200 kV. Furthermore, each sample has been modified with the addition of nanoparticles of different radii (50 nm and 100 nm) and at different interparticle distance (5 mm and 10 mm), considering an instant of time. The nanoparticles used are non-conductive and have been modelled as alumina (Al₂O₃). The geometry has been modelled according to IEC standard 60897, with a standard electrode gap distance of 25 mm. For an input supply voltage of 100 kV, the maximum electric field stresses obtained for the samples of synthetic vegetable oil, olive oil, and mineral oil are 5.08 ×10⁶ V/m, 5.11×10⁶ V/m and 5.62×10⁶ V/m, respectively. It is observed that for the unmodified samples, vegetable oils have a greater dielectric strength as compared to the conventionally used mineral oils because of their higher flash points and higher values of relative permittivity. Also, for the modified samples, the addition of nanoparticles inhibits the streamer propagation inside the dielectric medium and hence, serves to improve the dielectric properties of the medium.

Keywords: dielectric strength, finite element method, health index, nanotechnology, streamer propagation

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Authors: Cameron Hamilton, Walter Potter, Gerrit Hoogenboom, Ronald McClendon, Will Hobbs

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A model was constructed to predict the amount of solar radiation that will make contact with the surface of the earth in a given location an hour into the future. This project was supported by the Southern Company to determine at what specific times during a given day of the year solar panels could be relied upon to produce energy in sufficient quantities. Due to their ability as universal function approximators, an artificial neural network was used to estimate the nonlinear pattern of solar radiation, which utilized measurements of weather conditions collected at the Griffin, Georgia weather station as inputs. A number of network configurations and training strategies were utilized, though a multilayer perceptron with a variety of hidden nodes trained with the resilient propagation algorithm consistently yielded the most accurate predictions. In addition, a modeled DNI field and adjacent weather station data were used to bolster prediction accuracy. In later trials, the solar radiation field was preprocessed with a discrete wavelet transform with the aim of removing noise from the measurements. The current model provides predictions of solar radiation with a mean square error of 0.0042, though ongoing efforts are being made to further improve the model’s accuracy.

Keywords: artificial neural networks, resilient propagation, solar radiation, time series forecasting

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Authors: Manish Pal, Rumi Sutradhar

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Pavement surface unevenness plays a pivotal role on roughness index of road which affects on riding comfort ability. Comfort ability refers to the degree of protection offered to vehicle occupants from uneven elements in the road surface. So, it is preferable to have a lower roughness index value for a better riding quality of road users. Roughness is generally defined as an expression of irregularities in the pavement surface which can be measured using different equipment like MERLIN, Bump integrator, Profilometer etc. Among them Bump Integrator is quite simple and less time consuming in case of long road sections. A case study is conducted on low volume roads in West District in Tripura to determine roughness index (RI) using Bump Integrator at the standard speed of 32 km/h. But it becomes too tough to maintain the requisite standard speed throughout the road section. The speed of Bump Integrator (BI) has to lower or higher in some distinctive situations. So, it becomes necessary to convert these roughness index values of other speeds to the standard speed of 32 km/h. This paper highlights on that roughness index conversional model. Using SPSS (Statistical Package of Social Sciences) software a generalized equation is derived among the RI value at standard speed of 32 km/h and RI value at other speed conditions.

Keywords: bump integrator, pavement distresses, roughness index, SPSS

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Authors: Nissar Mohammad Karim, Norhayati Soin

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To ensure fast switching in high-K incorporated Complementary Metal Oxide Semiconductor (CMOS) transistors, the results on the basis of d (NBTI) by incorporating SiO2 dielectric with aged samples of CuO sol-gels have been reported. Precursor ageing has been carried out for 4 days. The minimum obtained refractive index is 1.0099 which was found after 3 hours of adhesive UV curing. Obtaining a low refractive index exhibits a low dielectric constant and hence a faster system.

Keywords: refractive index, Sol-Gel, precursor aging, aging

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Authors: Rodrigo M. Falleiro, Joaquim P. L. Parime, Luciano C. Santos, Rodrigo D. Silva

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The Cerrado biome is the most biodiverse savanna on the planet. Located in central Brazil, its preservation is seriously threatened by the advance of intensive agriculture and livestock. Conservation Units and Indigenous Lands are increasingly isolated and subject to mega wildfires. Among the characteristics of this savanna, we highlight the high rate of primary biomass production and the reduced occurrence of large grazing animals. In this biome, the predominant fauna is more dependent on the fruits produced by the dicotyledonous species in relation to other tropical savannas. Fire is a key element in the balance between mono and dicotyledons or between the arboreal and herbaceous strata. Therefore, applying fire regimes that maintain the balance between these strata without harming fruit production is essential in the conservation strategies of Cerrado's biodiversity. Recently, Integrated Fire Management has started to be implemented in Brazilian protected areas. As a result, management with prescribed burns has increasingly replaced strategies based on fire exclusion, which in practice have resulted in large wildfires, with highly negative impacts on fruit and fauna production. In the Indigenous Lands, these fires were carried out respecting traditional knowledge. The indigenous people showed great concern about the effects of fire on fruit plants and important animals. They recommended that the burns be carried out between April and May, as it would result in a greater production of edible fruits ("fruiting burning"). In other tropical savannas in the southern hemisphere, the preferential period tends to be later, in the middle of the dry season, when the grasses are dormant (June to August). However, in the Cerrado, this late period coincides with the flowering and sprouting of several important fruit species. To verify the best burning season, the present work evaluated the effects of fire on flowering and fruit production of theByrsonima sp., Mouriri pusa, Caryocar brasiliense, Anacardium occidentale, Pouteria ramiflora, Hancornia speciosa, Byrsonima verbascifolia, Anacardium humille and Talisia subalbens. The evaluations were carried out in the field, covering 31 Indigenous Lands that cover 104,241.18 Km², where 3,386 prescribed burns were carried out between 2015 and 2018. The burning periods were divided into early (carried out during the rainy season), modal or “fruiting” (carried out during the transition between seasons) and late (carried out in the middle of the dry season, when the grasses are dormant). The results corroborate the traditional knowledge, demonstrating that the modal burns result in higher rates of reproduction and fruit production. Late burns showed intermediate results, followed by early burns. We conclude that management strategies based mainly on forage production, which are usually applied in savannas populated by grazing ungulates, may not be the best management strategy for South American savannas. The effects of fire on fruit plants, which have a particular phenologicalsynchronization with the fauna cycle, also need to be observed during the prescription of burns.

Keywords: cerrado biome, fire regimes, native fruits, prescribed burns

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Authors: Mehrdad Kamali-Sanzighi, Maziar Kamali-Sanzighi

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The aim of this investigation is to study the phytoplankton and saprobic index at warm water fish ponds in the East of Golestan province, Gonbade Kavous city. Phytoplankton and ciliate sampling were done monthly during one season of culture. Finally, 39 genera from 7 classes of phytoplankton and 4 genera from the ciliate group were identified. Although, among different classes, Chlorophyceae, Cyanophyceae, Bacillariophyceae, Charophyceae, Chrysophyceae, Dinophyceae, and Euglenophyceae had the highest and lowest frequency percent of phytoplankton community with 23, 21, 20, 14, 11, 6 and 5 percent respectively. The results show that there are no significant differences between the saprobic index of different ponds (P > 0.05). But there are significant differences between the saprobic index value of different months and seasons during season culture (P < 0.05). Also, in current research, the saprobic index indicated the ß-mesosaprob water quality level. There was a general tends of decrease in the saprobic index value from the beginning to the end of the culture season. Parameters such as biomass increase of grower fishes, an increase of introduced chemical fertilizer and manure sedimentation, uneaten fish feed, fish fecal, and no regular exchangeable water resources are some of these changes' reasons.

Keywords: fish pond, Golestan Province, saprobi index, phytoplankton, water quality

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Authors: Yoftahe Nigussie

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This report presents a final year project pertaining to the design of Fire tube boiler for the purpose of producing saturated steam. The objective of the project is to produce saturated steam for different purpose with a capacity of 2000kg/h at 12bar design pressure by performing a design of a higher performance fire tube boiler that considered the requirements of cost minimization and parameters improvement. This is mostly done in selection of appropriate material for component parts, construction materials and production methods in different steps of analysis. In the analysis process, most of the design parameters are obtained by iterating with related formulas like selection of diameter of tubes with overall heat transfer coefficient optimization, and the other selections are also as like considered. The number of passes is two because of the size and area of the tubes and shell. As the analysis express by using heavy oil fuel no6 with a higher heating value of 44000kJ/kg and lower heating value of 41300kJ/kg and the amount of fuel consumed 140.37kg/hr. and produce 1610kw of heat with efficiency of 85.25%. The flow of the fluid is a cross flow because of its own advantage and the arrangement of the tube in-side the shell is welded with the tube sheet, and the tube sheet is attached with the shell and the end by using a gasket and weld. The design of the shell, using European Standard code section, is as like pressure vessel by considering the weight, including content and the supplementary accessories such as lifting lugs, openings, ends, man hole and supports with detail and assembly drawing.

Keywords: steam generation, external treatment, internal treatment, steam velocity

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Authors: Sabahat Zahra

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The purpose of this research is to present the changing global environment and its potential impacts on sustainable food and energy production at global level, particularly in Pakistan. The food and energy related-economic sector has been subjected to negative consequences due to recent extreme changes in weather conditions, particularly in developing countries. Besides continuous modifications in weather, population is also increasing by time, therefore it is necessary to take special steps and start effective initiatives to cope with the challenges of food and energy security to fight hunger and for economic stability of country. Severe increase in temperature and heat waves has also negative impacts on food production as well as energy sustainability. Energy (in terms of electricity) consumption has grown up than the production potential of the country as a consequence of increasing warm weather. Ultimately prices gone up when there is more consumption than production. Therefore, all these aspects of climate change are interrelated with socio-economic issues. There is a need to develop long-term policies on regional and national levels for maintainable economic growth. This research presents a framework-plan and recommendations for implementation needed to mitigate the potential threats due to global climate change sustainable food and energy production under climate change in the country.

Keywords: climate changes, energy security, food security, global climate change

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Authors: Viktor Novikov, Yuri Ruzhin

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The studies completed to-date on a relation of the Earth's seismicity and solar processes provide the fuzzy and contradictory results. For verification of an idea that solar flares can trigger earthquakes, we have analyzed a case of a powerful surge of solar flash activity early in September 2017 during approaching the minimum of 24th solar cycle was accompanied by significant disturbances of space weather. On September 6, 2017, a group of sunspots AR2673 generated a large solar flare of X9.3 class, the strongest flare over the past twelve years. Its explosion produced a coronal mass ejection partially directed towards the Earth. We carried out a statistical analysis of the catalogs of earthquakes USGS and EMSC for determination of the effect of solar flares on global seismic activity. New evidence of earthquake triggering due to the Sun-Earth interaction has been demonstrated by simple comparison of behavior of Earth's seismicity before and after the strong solar flare. The global number of earthquakes with magnitude of 2.5 to 5.5 within 11 days after the solar flare has increased by 30 to 100%. A possibility of electric/electromagnetic triggering of earthquake due to space weather disturbances is supported by results of field and laboratory studies, where the earthquakes (both natural and laboratory) were initiated by injection of electrical current into the Earth crust. For the specific case of artificial electric earthquake triggering the current density at a depth of earthquake, sources are comparable with estimations of a density of telluric currents induced by variation of space weather conditions due to solar flares. Acknowledgment: The work was supported by RFBR grant No. 18-05-00255.

Keywords: solar flare, earthquake activity, earthquake triggering, solar-terrestrial relations

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Authors: Ganesh B. Shinde, Vijaya B. Musande

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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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Authors: Tommy Krieger, Klaus Gruendler

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We present a novel approach for measuring democracy, which enables a very detailed and sensitive index. This method is based on Support Vector Machines, a mathematical algorithm for pattern recognition. Our implementation evaluates 188 countries in the period between 1981 and 2011. The Support Vector Machines Democracy Index (SVMDI) is continuously on the 0-1-Interval and robust to variations in the numerical process parameters. The algorithm introduced here can be used for every concept of democracy without additional adjustments, and due to its flexibility it is also a valuable tool for comparison studies.

Keywords: democracy, democracy index, machine learning, support vector machines

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Authors: V. Ziegler, F. Schneider, M. Pesch

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With the EDM264, GRIMM offers a solution for mobile short- and long-term measurements in outdoor areas and at production sites. For research as well as permanent areal observations on a near reference quality base. The model EDM264 features a powerful and robust measuring cell based on optical particle counting (OPC) principle with all the advantages that users of GRIMM's portable aerosol spectrometers are used to. The system is embedded in a compact weather-protection housing with all-weather sampling, heated inlet system, data logger, and meteorological sensor. With TSP, PM10, PM4, PM2.5, PM1, and PMcoarse, the EDM264 provides all fine dust fractions real-time, valid for outdoor applications and calculated with the proven GRIMM enviro-algorithm, as well as six additional dust mass fractions pm10, pm2.5, pm1, inhalable, thoracic and respirable for IAQ and workplace measurements. This highly versatile instrument performs real-time monitoring of particle number, particle size and provides information on particle surface distribution as well as dust mass distribution. GRIMM's EDM264 has 31 equidistant size channels, which are PSL traceable. A high-end data logger enables data acquisition and wireless communication via LTE, WLAN, or wired via Ethernet. Backup copies of the measurement data are stored in the device directly. The rinsing air function, which protects the laser and detector in the optical cell, further increases the reliability and long term stability of the EDM264 under different environmental and climatic conditions. The entire sample volume flow of 1.2 L/min is analyzed by 100% in the optical cell, which assures excellent counting efficiency at low and high concentrations and complies with the ISO 21501-1standard for OPCs. With all these features, the EDM264 is a world-leading dust monitor for precise monitoring of particulate matter and particle number concentration. This highly reliable instrument is an indispensable tool for many users who need to measure aerosol levels and air quality outdoors, on construction sites, or at production facilities.

Keywords: aerosol research, aerial observation, fence line monitoring, wild fire detection

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Authors: Ammar S. M. Moohialdin, Bambang T. Suhariadi, Mohsin Siddiqui

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This paper addresses the application of physiological status monitoring (PSM) for assessing the impact of harsh weather conditions on sports activities in universities in Saudi Arabia. Real sports measurement was conducted during sports activities such that the physiological status (HR and BR) of five students were continuously monitored by using Zephyr BioHarness^TM 3.0 sensors in order to identify the physiological bonds and zones. These bonds and zones were employed as indicators of the associated physiological risks of the performed sports activities. Furthermore, a short yes/no questionnaire was applied to collect information on participants’ health conditions and opinions of the applied PSM sensors. The results show the absence of a warning system as a protective aid for the hazardous levels of extremely hot and humid weather conditions that may cause dangerous and fatal circumstances. The applied formulas for estimating maximum HR provides accurate estimations for Maximum Heart Rate (HR_max). The physiological results reveal that the performed activities by the participants are considered the highest category (90–100%) in terms of activity intensity. This category is associated with higher HR, BR and physiological risks including losing the ability to control human body behaviors. Therefore, there is a need for immediate intervention actions to reduce the intensity of the performed activities to safer zones. The outcomes of this study assist the safety improvement of sports activities inside universities and athletes performing their sports activities. To the best of our knowledge, this is the first paper to represent a special case of the application of PSM technology for assessing sports activities in universities considering the impacts of harsh weather conditions on students’ health and safety.

Keywords: physiological status monitoring (PSM), heart rate (HR), breathing rate (BR), Arabian Gulf

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Authors: Nina Miklavčič, Urška Kugovnik, Natalia Galkina, Primož Ribarič, Rudi Vončina

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Today, the need for weather predictions is deeply rooted in the everyday life of people as well as it is in industry. The forecasts influence final decision-making processes in multiple areas, from agriculture and prevention of natural disasters to air traffic regulations and solutions on a national level for health, security, and economic problems. Namely, in Slovenia, alongside other existing forms of application, weather forecasts are adopted for the prognosis of electrical current transmission through powerlines. Meteorological parameters are one of the key factors which need to be considered in estimations of the reliable supply of electrical energy to consumers. And like for any other measured value, the knowledge about measurement uncertainty is also critical for the secure and reliable supply of energy. The estimation of measurement uncertainty grants us a more accurate interpretation of data, a better quality of the end results, and even a possibility of improvement of weather forecast models. In the article, we focused on the estimation of measurement uncertainty of the diagnostic microscale meteorological model CALMET. For the purposes of our research, we used a network of meteorological stations spread in the area of our interest, which enables a side-by-side comparison of measured meteorological values with the values calculated with the help of CALMET and the measurement uncertainty estimation as a final result.

Keywords: uncertancy, meteorological model, meteorological measurment, CALMET

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Authors: Suresh Kumar Bandooni, Mirana Laishram

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The Mid Himalaya of Garhwal Himalaya in Uttarakhand (India) has a complex Physiographic features withdiversified climatic conditions and therefore it is suspect to environmental vulnerability. Thenatural disasters and also anthropogenic activities accelerate the rate of environmental vulnerability. To analyse the environmental vulnerability, we have used geoinformatics technologies and numerical models and it is adoptedby using Spatial Principal Component Analysis (SPCA). The model consist of many factors such as slope, landuse/landcover, soil, forest fire risk, landslide susceptibility zone, human population density and vegetation index. From this model, the environmental vulnerability integrated index (EVSI) is calculated for Pasol Gad Watershed of Garhwal Himalaya for the years 1987, 2000, and 2013 and the Vulnerability is classified into five levelsi.e. Very low, low, medium, high and very highby means of cluster principle. The resultsforeco-environmental vulnerability distribution in study area shows that medium, high and very high levels are dominating in the area and it is mainly caused by the anthropogenic activities and natural disasters. Therefore, proper management forconservation of resources is utmost necessity of present century. It is strongly believed that participation at community level along with social worker, institutions and Non-governmental organization (NGOs) have become a must to conserve and protect the environment.

Keywords: eco-environment vulnerability, spatial principal component analysis, remote sensing, geographic information system, institutions, Himalaya

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Authors: Nissar Mohammad Karim, Norhayati Soin

Abstract:

To ensure fast switching in high-K incorporated Complementary Metal Oxide Semiconductor (CMOS) transistors, the results on the basis of d (NBTI) by incorporating SiO2 dielectric with aged samples of CuO sol-gels have been reported. Precursor ageing has been carried out for 4 days. The minimum obtained refractive index is 1.0099 which was found after 3 hours of adhesive UV curing. Obtaining a low refractive index exhibits a low dielectric constant and hence a faster system.

Keywords: refractive index, sol-gel, precursor ageing, metallurgical and materials engineering

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Authors: Le Xuan Cau

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Flash flood is occurred in short time rainfall interval: from 1 hour to 12 hours in small and medium basins. Flash floods typically have two characteristics: large water flow and big flow velocity. Flash flood is occurred at hill valley site (strip of lowland of terrain) in a catchment with large enough distribution area, steep basin slope, and heavy rainfall. The risk of flash floods is determined through Gridded Basin Flash Flood Potential Index (GBFFPI). Flash Flood Potential Index (FFPI) is determined through terrain slope flash flood index, soil erosion flash flood index, land cover flash floods index, land use flash flood index, rainfall flash flood index. Determining GBFFPI, each cell in a map can be considered as outlet of a water accumulation basin. GBFFPI of the cell is determined as basin average value of FFPI of the corresponding water accumulation basin. Based on GIS, a tool is developed to compute GBFFPI using ArcObjects SDK for .NET. The maps of GBFFPI are built in two types: GBFFPI including rainfall flash flood index (real time flash flood warning) or GBFFPI excluding rainfall flash flood index. GBFFPI Tool can be used to determine a high flash flood potential site in a large region as quick as possible. The GBFFPI is improved from conventional FFPI. The advantage of GBFFPI is that GBFFPI is taking into account the basin response (interaction of cells) and determines more true flash flood site (strip of lowland of terrain) while conventional FFPI is taking into account single cell and does not consider the interaction between cells. The GBFFPI Map of QuangNam, QuangNgai, DaNang, Hue is built and exported to Google Earth. The obtained map proves scientific basis of GBFFPI.

Keywords: ArcObjects SDK for NET, basin average value of FFPI, gridded basin flash flood potential index, GBFFPI map

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Authors: Lu Lin

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Urbanization has reshaped physical environment, energy consumption and carbon emission of the urban area. China is a typical developing country under a rapid urbanization process and is the world largest carbon emission country. This study aims to explore the correlation between urban form and carbon emission caused by urban energy consumption in China. 287 provincial-level and prefecture-level cities are studied in 2000, 2005, and 2010. Compact ratio index, shape index, and fractal dimension index are used to quantify urban form. Geographically weighted regression (GWR) model is employed to explore the relationship between urban form, energy consumption, and related carbon emission. The results show the average compact ratio index decreased from 2000 to 2010 which indicates urban in China sprawled. The average fractal dimension index increases by 3%, indicating the spatial layouts of China's cities were more complicated. The results by the GWR model show that shape index and fractal dimension index had a non-significant relationship with carbon emission by urban energy consumption. However, compact urban form reduced carbon emission. The findings of this study will help policy-makers make sustainable urban planning and reduce urban carbon emission.

Keywords: carbon emission, GWR model, urban energy consumption, urban form

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Authors: Olusegun D. Badewa, E. K. Tsado, A. S. Gana, K. D. Tolorunse, R. U. Okechukwu, P. Iluebbey, S. Ibrahim

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Farmers are faced with varying production challenges ranging from unstable weather due to climate change, low yield, malnutrition, cattle invasion, and bush fires that have always affected their livelihood. Research effort must therefore be centered on improving farmers’ livelihood, nutrition, and health by providing early bulking biofortified cassava varieties that could be harvested earlier with reasonable root yield and thereby preventing long stay of the crop on their farmland. This study evaluated cassava genotypes at different harvesting months of 3, 6, 9, and 12 months after planting in order to evaluate their bulking rate at different agroecology of Mokwa and Ubiaja. Data were collected on fresh storage root yield, Harvest index, and Dry matter content. It was shown from the study that traits FSRY, HI, and DM were significant for genotype and months after planting and variable among the genotype while location had no effect on the yield traits. Early bulking genotypes were not high yielding and showed discontinuity at some point across the months. The retrogression in yield performance across months had no effect on the highest yielding. Also, for all the genotypes and across evaluated months, FSRY reduces at 9 MAP due to a reduction in dry matter content during the same month, and the best performing genotype was the genotype IBA90581, followed by IBA120036, IBA130896, and IBA980581 while the least performing was genotype IBA130818.

Keywords: early bulking, dry mater, harvest index, high yielding, root yield

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Authors: Jan-Peter Mund, Christian Kind

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In view of the ongoing climate change and global warming, fires along railways in Germany are occurring more frequently, with sometimes massive consequences for railway operations and affected railroad infrastructure. In the absence of systematic studies within the infrastructure network of German Rail, little is known about the causes of such embankment fires. Since a further increase in these hazards is to be expected in the near future, there is a need for a sound knowledge of triggers and drivers for embankment fires as well as methodical knowledge of prediction tools. Two predictable future trends speak for the increasing relevance of the topic: through the intensification of the use of rail for passenger and freight transport (e.g..: doubling of annual passenger numbers by 2030, compared to 2019), there will be more rail traffic and also more maintenance and construction work on the railways. This research project approach uses satellite data to identify historical embankment fires along rail network infrastructure. The team links data from these fires with infrastructure and weather data and trains a machine-learning model with the aim of predicting fire hazards on sections of the track. Companies reflect on the results and use them on a pilot basis in precautionary measures.

Keywords: embankment fires, railway maintenance, machine learning, remote sensing, VIIRS data

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Authors: A. A. Dare, E. U. Iniegbedion

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Industrial furnaces generally involve enclosures of fire typically initiated by the combustion of gases. The fire leads to temperature distribution inside the enclosure. A proper understanding of the temperature and velocity distribution within the enclosure is often required for optimal design and use of the furnace. This study was therefore directed at numerical modeling of temperature distribution inside an enclosure as typical in a furnace. A mathematical model was developed from the conservation of mass, momentum and energy. The stream function-vorticity formulation of the governing equations was solved by an alternating direction implicit (ADI) finite difference technique. The finite difference formulation obtained were then developed into a computer code. This was used to determine the temperature, velocities, stream function and vorticity. The effect of the wall heat conduction was also considered, by assuming a one-dimensional heat flow through the wall. The computer code (MATLAB program) developed was used for the determination of the aforementioned variables. The results obtained showed that the transient temperature distribution assumed a uniform profile which becomes more chaotic with increasing time. The vertical velocity showed increasing turbulent behavior with time, while the horizontal velocity assumed decreasing laminar behavior with time. All of these behaviours were equally reported in the literature. The developed model has provided understanding of heat transfer process in an industrial furnace.

Keywords: heat source, modelling, enclosure, furnace

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Authors: Jean-Philippe Gagnon, Benjamin Saute, Stéphane Boubanga-Tombet

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Infrared thermal imaging is used for a wide range of applications, especially in the combustion domain. However, it is well known that most combustion gases such as carbon dioxide (CO₂), water vapor (H₂O), and carbon monoxide (CO) selectively absorb/emit infrared radiation at discrete energies, i.e., over a very narrow spectral range. Therefore, temperature profiles of most combustion processes derived from conventional broadband imaging are inaccurate without prior knowledge or assumptions about the spectral emissivity properties of the combustion gases. Using spectral filters allows estimating these critical emissivity parameters in addition to providing selectivity regarding the chemical nature of the combustion gases. However, due to the turbulent nature of most flames, it is crucial that such information be obtained without sacrificing temporal resolution. For this reason, Telops has developed a time-resolved multispectral imaging system which combines a high-performance broadband camera synchronized with a rotating spectral filter wheel. In order to illustrate the benefits of using this system to characterize combustion experiments, measurements were carried out using a Telops MS-IR MW on a very simple combustion system: a wood fire. The temperature profiles calculated using the spectral information from the different channels were compared with corresponding temperature profiles obtained with conventional broadband imaging. The results illustrate the benefits of the Telops MS-IR cameras for the characterization of laminar and turbulent combustion systems at a high temporal resolution.

Keywords: infrared, multispectral, fire, broadband, gas temperature, IR camera

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Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

Abstract:

Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

Procedia PDF Downloads 131

Authors: Guangzhuang Yu, Chun-Chu Liu

Abstract:

With the advent of the Internet era in recent years, social music education has gradually shifted from the original entity education mode to the mode of entity plus network teaching. No matter for school music education, professional music education or social music education, the teaching quality is the most important evaluation index. Regarding the research on teaching quality evaluation, scholars at home and abroad have contributed a lot of research results on the basis of multiple methods and evaluation subjects. However, to our best knowledge the complete evaluation model for the virtual teaching interaction mode of the emerging network music education Application (APP) has not been established. This research firstly found out the basic dimensions that accord with the teaching quality required by the three parties, constructing the quality evaluation index system; and then, on the basis of expounding the connotation of each index, it determined the weight of each index by using method of fuzzy analytic hierarchy process, providing ideas and methods for scientific, objective and comprehensive evaluation of the teaching quality of network education APP.

Keywords: network music education APP, teaching quality evaluation, index and connotation

Procedia PDF Downloads 121

Authors: Siti Nur Aida Mario, Farah Hafifee Ahmad, Rudy Tawie

Abstract:

Soil Stabilization has been widely implemented in the construction industry nowadays. Peat soil is well known as one of the most problematic soil among the engineers. The procedures need to take into account both physical and engineering properties of the stabilized peat soil. This paper presents a result of plasticity index and hardening of treated peat soil with various dosage of additives. In order to determine plasticity of the treated peat soil, atterberg limit test which comprises plastic limit and liquid limit test has been conducted. Determination of liquid limit in this experimental study is by using cone penetrometer. Vicat testing apparatus has been used in the hardening test which the penetration of the plunger is recorded every one hour for 24 hours. The results show that the plasticity index of peat soil stabilized with 80% FAAC and 20% OPC has the lowest plasticity index and recorded the fastest initial setting time. The significant of this study is to promote greener solution for future soil stabilization industry.

Keywords: additives, hardening, peat soil, plasticity index, soil stabilization

Procedia PDF Downloads 324

Authors: Muhammad Tufail, Jawad Hussain, Hammad Hussain, Imran Hafeez, Naveed Ahmad

Abstract:

Road safety performance index is a composite index which combines various indicators of road safety into single number. Development of a road safety performance index using appropriate safety performance indicators is essential to enhance road safety. However, a road safety performance index in developing countries has not been given as much priority as needed. The primary objective of this research is to develop a general Road Safety Performance Index (RSPI) for developing countries based on the facility as well as behavior of road user. The secondary objectives include finding the critical inputs in the RSPI and finding the better method of making the index. In this study, the RSPI is developed by selecting four main safety performance indicators i.e., protective system (seat belt, helmet etc.), road (road width, signalized intersections, number of lanes, speed limit), number of pedestrians, and number of vehicles. Data on these four safety performance indicators were collected using observation survey on a 20 km road section of the National Highway N-125 road Taxila, Pakistan. For the development of this composite index, two methods are used: a) Principal Component Analysis (PCA) and b) Equal Weighting (EW) method. PCA is used for extraction, weighting, and linear aggregation of indicators to obtain a single value. An individual index score was calculated for each road section by multiplication of weights and standardized values of each safety performance indicator. However, Simple Average technique was used for weighting and linear aggregation of indicators to develop a RSPI. The road sections are ranked according to RSPI scores using both methods. The two weighting methods are compared, and the PCA method is found to be much more reliable than the Simple Average Technique.

Keywords: indicators, aggregation, principle component analysis, weighting, index score

Procedia PDF Downloads 150

Authors: Isaac Kayode Ogunlade

Abstract:

Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

Procedia PDF Downloads 86